Modeling Jumps and Volatility of the Indian Stock Market Using High-Frequency Data

被引：0

作者：

Sen R. ^{[1
]}

Mehrotra P. ^{[2
]}

机构：

[1] Applied Statistics Unit, Indian Statistical Institute, Chennai Centre, MGR Knowledge City, CIT Campus, Taramani, Chennai, 600113, Tamil Nadu

[2] Financial Modeling Team, HSBC Analytics, Bangalore

来源：

Journal of Quantitative Economics | 2016年 / 14卷 / 1期

关键词：

Asymmetric power ARCH; High frequency financial data; Jump detection; Realized volatility;

D O I：

10.1007/s40953-016-0028-5

中图分类号：

学科分类号：

摘要：

Recent advancements in technology have led to wide availability of high-frequency financial data. The aim of this paper is to study the behavior of the Indian stock market. In particular, we analyze the returns at 5 min interval from NSE using the index NIFTY and the stocks State Bank of India and Infosys. A non-parametric approach is taken to detect jumps in the return process. The analysis shows that index jumps relate very closely with the general market news and announcements while individual stock jumps are associated with company specific news. We find that volatility of the market is best captured by asymmetric power ARCH models. © 2016, The Indian Econometric Society.

引用

页码：137 / 150

页数：13

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